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Antiretroviral therapy outcomes among adolescents and youth in rural Zimbabwe
Global Health Sciences Literature Digest
Published January 22, 2013
Journal Article

Bygrave H, Mtangirwa J, Ncube K, Ford N, Kranzer K, Munyaradzi D. Antiretroviral therapy outcomes among adolescents and youth in rural Zimbabwe. PLoS One. 2012;7(12):e52856. doi: 10.1371/journal.pone.0052856. Epub 2012 Dec 20.

Objective

To compare retention in care outcomes in several age strata of young people receiving antiretroviral therapy (ART) in a rural setting in Zimbabwe.

Setting

Decentralized primary care clinics (n=25) in Buhera district, Manicaland, Zimbabwe.

Study Design

Retrospective analysis of routinely-collected clinical data.

Population

All HIV-infected persons ages 10-30 years, with CD4 <200 cells/µL, World Health Organization (WHO) clinical stage 4 conditions or tuberculosis (TB), who initiated ART between January 2005 and June 2008.

Main Outcome Measures

Rates of mortality and loss to follow-up (LTFU).

Methods

Data were anonymized and entered prospectively into an electronic patient register. The cohort was stratified into four age groups: Young adolescents (ages 10 to 15 years), adolescents (ages 15.1 to 19 years), young adults (ages 19.1 to 24 years) and older adults (ages 24.1 to 29.9 years). LTFU was defined as non-attendance for a period of three months after the last ART prescription had been completed. Death was defined as any death while in treatment.

Baseline characteristics were described using median and interquartile ranges (IQR) for continuous variables and counts and percentages for categorical variables. Survival analysis was used to estimate rates of mortality and LTFU stratified by age group. Entry time into the cohort was the date of ART initiation. Endpoints were the time from ART initiation to death or LTFU. Hazard ratios comparing different age groups were estimated, adjusting for sex and for baseline CD4 count.

Results

A total of 898 patients was included in the analysis. While there was a fairly equal proportion of males and females among the young adolescents (109:112, 49.3% male) and adolescents (40:45, 47.1% male), this ratio was not maintained in the young adult (14% male) or older adult (19.6% male) age strata. Median duration on ART was 441 days (IQR 257 to 643). This was highest for young adolescents (484 days, IQR 334 to 755). CD4 cell counts were missing for 294 (32.7%) patients. The proportion of missing CD4 cell counts was similar across all age categories. Median CD4 cell count was <200 cells/µL across all age categories and was lowest for adolescents (median CD4 102 cells/µL, IQR 21-184 cells/µL).

Outcome: Death

Overall, mortality was 6.2 per 100 person-years (PY) (95% confidence interval [CI] 4.9 to 7.7 PY). Older adults had the highest mortality (7.7 per 100 PY, 95% CI 5.8 to 10.4 PY). Mortality was lower in young adults (6.6 per 100 PY, 95% CI 3.7 to 11.9 PY), adolescents (5.4 per 100 PY, 95% CI 2.4 to 12.1 PY), and young adolescents (3.6 per 100 PY, 95% CI 2.0 to 6.3 PY).

Adjusted hazard ratios (aHR) for death were significantly higher in older adults compared to young adolescents (aHR 2.25, 95%CI 1.17 to 4.35). There were no significant differences observed in the hazard of death comparing any of the other age groups with young adolescents. Results were similar when adjusting for baseline immune deficiency, using a separate category for missing CD4 cell count, or restricting the analysis to the complete dataset.

Outcome: LTFU

Overall, the rate of LTFU was 8.3 per 100 PY (95% CI 6.8 to 10.1 PY). Young adults had the highest rates of LTFU (16.8 per 100 PY, 95% CI 11.6 to 24.3 PY). LTFU was lower in adolescents (10.9 per 100 PY, 95% CI 6.2 to 19.1 PY), older adults (7.7 per 100 PY, 95% CI 5.8 to 10.4 PY), and young adolescents (4.2 per 100 PY, 95% CI 2.5 to 7.0 PY).

In contrast to the results for mortality, young adults and adolescents had two to three times higher hazards of LTFU compared to young adolescents (young adults: aHR 3.35, 95% CI 1.73 to 6.49; adolescents: aHR 2.54, 95% CI 1.17 to 5.49). When estimating the risk for either LTFU or death, young adults had the highest hazard (aHR 2.70, 95% CI 1.62 to 4.52). The results remained largely unchanged when adjusting for baseline CD4 count both when a separate category was used for missing CD4 counts or when the analysis was restricted to the complete dataset.

Rates of death and LTFU (from the article)

Rates of death and LTFU (from the article)

Conclusions

The authors conclude that in resource-limited rural settings, young adults are at the highest risk of being lost from care. The authors suggest that adapting adherence support and service delivery models for this group should be a priority to avoid treatment interruptions, development of resistance and increased morbidity within this age group.

Risk of Bias

The overall risk of bias in this study is high. The risk of bias is inherently high in observational studies, particularly small ones, and particularly in studies where data are analyzed retrospectively. The authors additionally note that incomplete baseline CD4 data did not allow for appropriate adjustment in the analyses. The economic and political situation in Zimbabwe during the study period as well as changes in service delivery may also have had an impact on retention rates.

In Context

Patients on ART must remain in care in order for therapy to be effective. It has proven difficult to ensure that patients remain in care, particularly in resource-limited settings.(1, 2, 3, 4, 5) There are many factors associated with loss to care, including travel distances and costs, discouragement and stigma; but also including improved health, and the desire to return to a normal life.(6, 7, 8, 9, 10, 11, 12, 13) Recently-published qualitative research from three countries in sub-Saharan Africa found that missed clinical visits, whether intentional or unintentional, often lead to a feeling of shame, the fear of being considered a bad patient and a reluctance to return to care. This reluctance weakened patients' feelings of connectedness to care, which lead in turn to their disengagement from care.(14)

Programmatic Implications

In addition to maintaining efforts to ensure adherence and retention in care, health care providers should consider adapting models of service delivery so that barriers to re-entering care are minimized.

References

  1. Rosen S, Fox MP, Gill CJ (2007) Patient retention in antiretroviral therapy programs in sub-Saharan Africa: a systematic review. PLoS Med 4: e298. doi:10.1371/journal.pmed.0040298
  2. Fox MP, Rosen S (2010) Patient retention in antiretroviral therapy programs up to three years on treatment in sub-Saharan Africa, 2007-2009: systematic review. Trop Med Int Health 15 (Suppl 1): 1-15.
  3. Cornell M, Grimsrud A, Fairall L, Fox MP, van Cutsem G, et al. (2010) Temporal changes in programme outcomes among adult patients initiating antiretroviral therapy across South Africa, 2002-2007. AIDS 24: 2263-2270.
  4. Tassie JM, Baijal P, Vitoria MA, Alisalad A, Crowley SP, et al. (2010) Trends in retention on antiretroviral therapy in national programs in low-income and middle-income countries. J Acquir Immune Defic Syndr 54: 437-441.
  5. Koole O, Kalenga L, Kiumbu M, Menten J, Ryder RW, et al. (2012) Retention in an NGO supported antiretroviral program in the Democratic Republic of Congo. PLoS ONE 7: e40971. doi:10.1371/journal.pone.0040971
  6. Maskew M, MacPhail P, Menezes C, Rubel D (2009) Loss to follow up: contributing factors and challenges in South African patients on antiretroviral therapy. S Afr Med J 97: 853-857.
  7. Miller CM, Ketlhapile M, Rybasack-Smith H, Rosen S (2010) Why are antiretroviral treatment patients lost to follow-up? A qualitative study from South Africa. Trop Med Int Health 15 (Suppl 1): 48-54.
  8. Roura M, Busza J, Wringe A, Mbata D, Urassa M, et al. (2009) Barriers to sustaining antiretroviral treatment in Kisesa, Tanzania: a follow-up study to understand attrition from the antiretroviral program. AIDS Patient Care STDS 23: 203-210.
  9. Krebs DW, Chi BH, Mulenga Y, Morris M, Cantrell RA, et al. (2008) Community-based follow-up for late patients enrolled in a district-wide programme for antiretroviral therapy in Lusaka, Zambia. AIDS Care 20: 311-317.
  10. McGuire M, Munyenyembe T, Szumilin E, Heinzelmann A, Paih ML, et al. (2010) Vital status of pre-ART and ART patients defaulting from care in rural Malawi. Trop Med Int Health 15 (Suppl 1): 55-62.
  11. Rosen S, Ketlhapile M (2010) Cost of using a patient tracer to reduce loss to follow-up and ascertain patient status in a large antiretroviral therapy program in Johannesburg, South Africa. Trop Med Int Hlth 15 (Suppl 1): 98-104.
  12. Alamo ST, Colebunders R, Ouma J, Sunday P, Wagner G, et al. (2012) Return to normal life after AIDS as a reason for loss to follow-up in a community-based antiretroviral treatment program. J Acquir Immune Defic Syndr 60: e36-e45.
  13. Merten S, Kenter E, McKenzie O, Musheke M, Ntalasha H, et al. (2010) Patient-reported barriers and drivers of adherence to antiretrovirals in sub-Saharan Africa: a meta-ethnography. Trop Med Int Health 15 (Suppl 1): 16-33.
  14. Ware NC, Wyatt MA, Geng EH, Kaaya SF, Agbaji OO, et al. (2013) Toward an Understanding of Disengagement from HIV Treatment and Care in Sub-Saharan Africa: A Qualitative Study. PLoS Med 10(1): e1001369. doi:10.1371/journal.pmed.1001369